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Fix linkchecker doc errors
Also includes small doc fixes.
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@ -193,7 +193,7 @@ impl<T> [T] {
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// with k distinct elements, the expected time to sort the data is *O(*n* log(*k*))*.
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/// with k distinct elements, the expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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@ -252,7 +252,7 @@ impl<T> [T] {
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// with k distinct elements, the expected time to sort the data is *O(*n* log(*k*))*.
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/// with k distinct elements, the expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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@ -298,7 +298,7 @@ impl<T> [T] {
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// The current implementation is based on [driftsort] by Orson Peters and Lukas Bergdoll, which
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// combines the fast average case of quicksort with the fast worst case and partial run
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// detection of mergesort, achieving linear time on fully sorted and reversed inputs. On inputs
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/// with k distinct elements, the expected time to sort the data is *O(*n* log(*k*))*.
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/// with k distinct elements, the expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// The auxiliary memory allocation behavior depends on the input length. Short slices are
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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/// handled without allocation, medium sized slices allocate `self.len()` and beyond that it
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@ -2893,7 +2893,7 @@ impl<T> [T] {
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// expected time to sort the data is *O(*n* log(*k*))*.
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/// expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// slice is partially sorted.
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/// slice is partially sorted.
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@ -2950,7 +2950,7 @@ impl<T> [T] {
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// expected time to sort the data is *O(*n* log(*k*))*.
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/// expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// slice is partially sorted.
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/// slice is partially sorted.
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@ -2994,7 +2994,7 @@ impl<T> [T] {
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// The current implementation is based on [ipnsort] by Lukas Bergdoll and Orson Peters, which
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// combines the fast average case of quicksort with the fast worst case of heapsort, achieving
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// linear time on fully sorted and reversed inputs. On inputs with k distinct elements, the
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/// expected time to sort the data is *O(*n* log(*k*))*.
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/// expected time to sort the data is *O(*n* \* log(*k*))*.
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///
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///
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// slice is partially sorted.
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/// slice is partially sorted.
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@ -3042,8 +3042,8 @@ impl<T> [T] {
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// for all inputs.
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/// for all inputs.
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///
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///
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/// It is typically faster than sorting, except in a few special cases, e.g., when the slice is
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// nearly fully sorted, where [`slice::sort`] may be faster.
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/// slice is nearly fully sorted, where `slice::sort` may be faster.
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///
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///
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/// [`sort_unstable`]: slice::sort_unstable
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/// [`sort_unstable`]: slice::sort_unstable
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///
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///
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@ -3103,8 +3103,8 @@ impl<T> [T] {
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// for all inputs.
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/// for all inputs.
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///
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///
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/// It is typically faster than sorting, except in a few special cases, e.g., when the slice is
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// nearly fully sorted, where [`slice::sort`] may be faster.
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/// slice is nearly fully sorted, where `slice::sort` may be faster.
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///
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///
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/// [`sort_unstable`]: slice::sort_unstable
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/// [`sort_unstable`]: slice::sort_unstable
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///
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///
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@ -3168,8 +3168,8 @@ impl<T> [T] {
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// Median of Medians using Tukey's Ninther for pivot selection, which guarantees linear runtime
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/// for all inputs.
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/// for all inputs.
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///
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///
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/// It is typically faster than sorting, except in a few special cases, e.g., when the slice is
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/// It is typically faster than stable sorting, except in a few special cases, e.g., when the
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/// nearly fully sorted, where [`slice::sort`] may be faster.
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/// slice is nearly fully sorted, where `slice::sort` may be faster.
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///
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///
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/// [`sort_unstable`]: slice::sort_unstable
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/// [`sort_unstable`]: slice::sort_unstable
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///
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///
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